Triple

T657014
Position Surface form Disambiguated ID Type / Status
Subject George Clooney E11669 entity
Predicate givenName P17 FINISHED
Object George E22107 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: George | Statement: [George Clooney, givenName, George]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George
Context triple: [George Clooney, givenName, George]
  • A. George
    George is a town in South Africa’s Western Cape province, known as a gateway to the Garden Route and for its scenic mountains and forests.
  • B. George chosen
    George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
  • C. Henry
    Henry is the given name of Henry A. Kissinger, the influential American diplomat and political scientist who served as U.S. Secretary of State and National Security Advisor.
  • D. Edward
    Edward is a masculine given name of English origin, historically associated with kings of England and notable figures such as U.S. Senator Edward M. Kennedy.
  • E. Charles
    Charles is a masculine given name of Germanic origin that has been widely used across Europe and the English-speaking world, borne by numerous historical figures, royalty, and notable individuals.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f4e87408190b5276d2b913d0426 completed March 1, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad3072c3a881908c33159cdd55ae0b completed March 8, 2026, 8:16 a.m.
Created at: March 1, 2026, 7:36 p.m.